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排序方式: 共有325条查询结果,搜索用时 31 毫秒
1.
Catalysis Letters - In this work we studied the reactivity of the Trifluoroacetic acid hydroxylamine system in the one step salt free synthesis of amides from ketones. A particular regards was paid... 相似文献
2.
Unusual extended corrosion phenomena were detected in a distillation column made in AISI type 316 stainless steel (UNS S31600) of a plant for natural pectins extraction from citrus. The column was the first of a series of two distillation columns representing the unit core. Corrosion problems were observed only in that column and mainly along the surface of the trays located in the lower section of the column. The phenomenon was observed subsequently to a modification of the original plant layout that caused an increase of the operating temperatures and turbulence of the process stream inside the column. 相似文献
3.
DellaGreca M Isidori M Lavorgna M Monaco P Previtera L Zarrelli A 《Journal of chemical ecology》2004,30(4):867-879
Twenty-five 9,10-dihydrophenanthrenes, four phenanthrenes, a dihydrodibenzoxepin, and a pyrene, isolated from the wetland plant Juncus acutus, were tested to detect their effects on the green alga Selenastrum capricornutum. Nine of the compounds were isolated and identified for the first time. Most of the compounds caused inhibition of algal growth. The 9,10-dihydrophenanthrenes 1, 5, 21, and 22 were the most active. 相似文献
4.
Recently, the use of lime mortars in the restoration of historic buildings has found a renewed interest because they can guarantee the required mechanical, chemical and physical compatibility with the existing substrate. Spontaneous occurrence of self-healing phenomena in lime-based mortars is well known; the possibility of engineering the self-healing capacity, through tailored additions, is therefore of the utmost interest with the aim of enhancing the durability of the building masonry restoration works. This work proposes a system for the evaluation of the self-healing capacity with reference to traditional and advanced lime mortars. The autogenous healing capacity of a reference lime mortar has been first of all evaluated. Then, the possibility of engineering the aforementioned capacity has also assessed, through both commercial crystalline admixtures and tailored encapsulated additives. These should work according to a twofold mechanism: first, the coated granules envelope a core of lime mortar with purpose of making it inert during the hardening phase. Secondly, once the coated granules rupture upon cracking and damage of the mortar, the reactive binder is released and undergoes a delayed hardening, which is responsible of the healing phenomena. The results show that the mortar is able to heal micro-cracks; moreover, the addition of the crystalline admixture enhances this capacity. The different kinds of employed coated granules were also able to induce a sensible self-healing, but they decrease the instantaneous compressive strength. 相似文献
5.
Jens Laube Valentin Baric Samir Salameh Lutz Mädler Lucio Colombi Ciacchi 《Granular Matter》2018,20(2):28
We develop a novel coarse-grained contact model for Discrete Element Method simulations of \(\hbox {TiO}_2\) nanoparticle films subjected to mechanical stress. All model elements and parameters are derived in a self-consistent and physically sound way from all-atom Molecular Dynamics simulations of interacting particles and surfaces. In particular, the nature of atomic-scale friction and dissipation effects is taken into account by explicit modelling of the surface features and water adsorbate layers that strongly mediate the particle-particle interactions. The quantitative accuracy of the coarse-grained model is validated against all-atom simulations of \(\hbox {TiO}_2\) nanoparticle agglomerates under tensile stress. Moreover, its predictive power is demonstrated with calculations of force-displacement curves of entire nanoparticle films probed with force spectroscopy. The simulation results are compared with Atomic Force Microscopy and Transmission Electron Microscopy experiments. 相似文献
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7.
Charlotte Szewczykowski Christian Mardin Marianna Lucio Gerd Wallukat Jakob Hoffmanns Thora Schrder Franziska Raith Lennart Rogge Felix Heltmann Michael Moritz Lorenz Beitlich Julia Schottenhamml Martin Herrmann Thomas Harrer Marion Ganslmayer Friedrich E. Kruse Martin Krter Jochen Guck Robert Lmmer Matthias Zenkel Andreas Gießl Bettina Hohberger 《International journal of molecular sciences》2022,23(13)
Long COVID (LC) describes the clinical phenotype of symptoms after infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnostic and therapeutic options are limited, as the pathomechanism of LC is elusive. As the number of acute SARS-CoV-2 infections was and is large, LC will be a challenge for the healthcare system. Previous studies revealed an impaired blood flow, the formation of microclots, and autoimmune mechanisms as potential factors in this complex interplay. Since functionally active autoantibodies against G-protein-coupled receptors (GPCR-AAbs) were observed in patients after SARS-CoV-2 infection, this study aimed to correlate the appearance of GPCR-AAbs with capillary microcirculation. The seropositivity of GPCR-AAbs was measured by an established cardiomyocyte bioassay in 42 patients with LC and 6 controls. Retinal microcirculation was measured by OCT–angiography and quantified as macula and peripapillary vessel density (VD) by the Erlangen-Angio Tool. A statistical analysis yielded impaired VD in patients with LC compared to the controls, which was accentuated in female persons. A significant decrease in macula and peripapillary VD for AAbs targeting adrenergic β2-receptor, MAS-receptor angiotensin-II-type-1 receptor, and adrenergic α1-receptor were observed. The present study might suggest that a seropositivity of GPCR-AAbs can be linked to an impaired retinal capillary microcirculation, potentially mirroring the systemic microcirculation with consecutive clinical symptoms. 相似文献
8.
Bibiana C. Mota Nathan Ashburner Laura Abelleira-Hervas Liyueyue Liu Robertas Aleksynas Lucio Claudio Rovati Gianfranco Caselli Magdalena Sastre 《International journal of molecular sciences》2022,23(13)
Recent evidence suggests that I2-imidazoline ligands have neuroprotective properties in animal models of neurodegeneration, such as Alzheimer’s disease (AD). We recently demonstrated that the I2-ligand BU224 reversed memory impairments in AD transgenic mice and this effect was not because of reductions in amyloid-β (Aβ) deposition. In this study, our aim was to determine the therapeutic potential of the powerful analgesic I2-imidazoline ligand CR4056 in the 5xFAD model of AD, since this ligand has been proven to be safely tolerated in humans. Sub-chronic oral administration of CR4056 (30 mg/kg for 10 days) led to an improvement in recognition memory in 6-month-old 5xFAD mice, but not in wild-type littermates, without affecting Aβ levels or deposition. Our results also revealed a change in the profile of microglia by CR4056, resulting in a suppression of pro-inflammatory activated microglia, but increased the density of astrocytes and the expression of ApoE, which is mainly produced by these glial cells. In addition, CR4056 restored fibrinogen extravasation, affecting the distribution of markers of astrocytic end feet in blood vessels. Therefore, these results suggest that CR4056 protects against Aβ-mediated neuroinflammation and vascular damage, and offers therapeutic potential at any stage of AD. 相似文献
9.
10.
Lucio F.M. Mota Sara Pegolo Toshimi Baba Francisco Peñagaricano Gota Morota Giovanni Bittante Alessio Cecchinato 《Journal of dairy science》2021,104(7):8107-8121
Fourier-transform infrared (FTIR) spectroscopy is a powerful high-throughput phenotyping tool for predicting traits that are expensive and difficult to measure in dairy cattle. Calibration equations are often developed using standard methods, such as partial least squares (PLS) regression. Methods that employ penalization, rank-reduction, and variable selection, as well as being able to model the nonlinear relations between phenotype and FTIR, might offer improvements in predictive ability and model robustness. This study aimed to compare the predictive ability of 2 machine learning methods, namely random forest (RF) and gradient boosting machine (GBM), and penalized regression against PLS regression for predicting 3 phenotypes differing in terms of biological meaning and relationships with milk composition (i.e., phenotypes measurable directly and not directly in milk, reflecting different biological processes which can be captured using milk spectra) in Holstein-Friesian cattle under 2 cross-validation scenarios. The data set comprised phenotypic information from 471 Holstein-Friesian cows, and 3 target phenotypes were evaluated: (1) body condition score (BCS), (2) blood β-hydroxybutyrate (BHB, mmol/L), and (3) κ-casein expressed as a percentage of nitrogen (κ-CN, % N). The data set was split considering 2 cross-validation scenarios: samples-out random in which the population was randomly split into 10-folds (8-folds for training and 1-fold for validation and testing); and herd/date-out in which the population was randomly assigned to training (70% herd), validation (10%), and testing (20% herd) based on the herd and date in which the samples were collected. The random grid search was performed using the training subset for the hyperparameter optimization and the validation set was used for the generalization of prediction error. The trained model was then used to assess the final prediction in the testing subset. The grid search for penalized regression evidenced that the elastic net (EN) was the best regularization with increase in predictive ability of 5%. The performance of PLS (standard model) was compared against 2 machine learning techniques and penalized regression using 2 cross-validation scenarios. Machine learning methods showed a greater predictive ability for BCS (0.63 for GBM and 0.61 for RF), BHB (0.80 for GBM and 0.79 for RF), and κ-CN (0.81 for GBM and 0.80 for RF) in samples-out cross-validation. Considering a herd/date-out cross-validation these values were 0.58 (GBM and RF) for BCS, 0.73 (GBM and RF) for BHB, and 0.77 (GBM and RF) for κ-CN. The GBM model tended to outperform other methods in predictive ability around 4%, 1%, and 7% for EN, RF, and PLS, respectively. The prediction accuracies of the GBM and RF models were similar, and differed statistically from the PLS model in samples-out random cross-validation. Although, machine learning techniques outperformed PLS in herd/date-out cross-validation, no significant differences were observed in terms of predictive ability due to the large standard deviation observed for predictions. Overall, GBM achieved the highest accuracy of FTIR-based prediction of the different phenotypic traits across the cross-validation scenarios. These results indicate that GBM is a promising method for obtaining more accurate FTIR-based predictions for different phenotypes in dairy cattle. 相似文献